Cascading Defaults and Systemic Risk of a Banking System
Jin‐Chuan Duan, Changhao Zhang
Abstract
Jin‐Chuan Duan, Changhao Zhang
Abstract
Systemic risk of a banking system arises from cascading defaults due to interbank linkages. Any large negative external shock can in principle trigger cascading defaults, but shocks to systematic risk factors, as opposed to banks ' idiosyncratic elements, are more likely to drive cascading defaults and hence to cause higher systemic risk. This paper proposes a structural model for a banking system in which bank assets are subject to both systematic and idiosyncratic risks and bank liabilities contain interbank exposures which may or may not be subject to netting. This model allows us to dene two useful measures: systemic exposure and systemic fragility. The former characterizes the expected losses due to interbank linkages under some prescribed macro stress scenario, whereas the latter measures the pervasiveness of bank defaults under the same condition. In addition, we are able to compute marginal systemic risk measures and use them to rank banks according to their individual contributions to systemic risk. Our model is conducive to examining potential impacts on systemic risk under different banking network configurations. We devise a novel bridge sampling technique specifically for computing these two systemic risk measures, and obtain data and estimates for a network of 15 British banks. Our results are
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Systemic risk of a banking system arises from cascading defaults due to interbank linkages. Any large negative external shock can in principle trigger cascading defaults, but shocks to systematic risk factors, as opposed to banks ' idiosyncratic elements, are more likely to drive cascading defaults and hence to cause higher systemic risk. This paper proposes a structural model for a banking system in which bank assets are subject to both systematic and idiosyncratic risks and bank liabilities contain interbank exposures which may or may not be subject to netting. This model allows us to dene two useful measures: systemic exposure and systemic fragility. The former characterizes the expected losses due to interbank linkages under some prescribed macro stress scenario, whereas the latter measures the pervasiveness of bank defaults under the same condition. In addition, we are able to compute marginal systemic risk measures and use them to rank banks according to their individual contributions to systemic risk. Our model is conducive to examining potential impacts on systemic risk under different banking network configurations. We devise a novel bridge sampling technique specifically for computing these two systemic risk measures, and obtain data and estimates for a network of 15 British banks. Our results are
Key concepts: Systemic risk, Default, Business, Systematic risk, Shock (circulatory), Cascading failure, Credit risk, Financial system